Managing Drone Data: Choosing the Right Data Service Provider

1|Copyright 2018 – Skylogic Research, LLC
MANAGING DRONE
DATA: CHOOSING THE
RIGHT DATA SERVICE
PROVIDER
September 6, 2018
Presented by Colin Snow

About Skylogic Research, LLC is a research, content, and advisory services firm
supporting all participants in the commercial unmanned aircraft systems (UAS)
industry.
We help companies make critical investment decisions with confidence by providing
research-based insights on the commercial drone markets.
Our focus is on the needs of three constituents:
• Manufacturers, suppliers, and business service providers – who need research and insight
into buyer needs
• Buyers of UAS technology and services – to help inform their acquisition decisions
• Investors – who need to distinguish technical and market viability
This focus, plus research as a foundation and reach into a community of more than 90,000
business executives and innovators through social media and media partnerships, allows us to
deliver a high-value, low-risk method for achieving optimal understanding.
Drone Analyst® is the registered trademark and brand name and trademark of Skylogic
Research, LLC
Learn more:
Web http://droneanalyst.com
Twitter @droneanalyst
Email colin@droneanalyst.com

5,700 clients worldwide
Research,content,oradviceto:

Objectives Who are the major providers and what’s their focus?
How to determine the value of the services they provide?
What questions should you be asking when comparing offerings?
What’s the best way to integrating a service into your existing workflow
so that it simplifies your operations and save costs?

Topics Workflow and the role of software in drone operations
Characteristics of drone data (raw and processed)
Analytics and AI
Major vendors
Pricing
IT best practices
Five selection tips

Workflow
Flight
Planning
•Site selection
•Airspace
•Flight path
•Overlap
•Capture
parameters
Data
Acquisition
•Aircraft /
Platforms
•Sensors
•Computer
vision
•Embedded AI
Data
Processing
•On-board
•Cloud-based
•Post-
processing
•Live
streaming
•Storage
•Images/
video
•Photo-
grammetry
•3D models
•NDVI/ index
maps
•Machine
learning/AI
•Mobile
•PC
•Real-time data
•APIs
Data
Visualization
Data
Presentation
Operations
•Flight logging
•Fleet
management
•SOPs
•Safety checks
•Pre-flight / post-
flight
maintenance
•Insurance
Drone industry software will need to support a standardized but
flexible workflow to cover the various operation types with built-in
functionality or an ecosystem of partnerships.
Operation Types:
Standardized Workflow
Day Night Over People BVLOS Source:: Ardenna, Frost and Sullivan,, and Skylogic Research
•Asset
Management
(EAM)
•Operations
Management
•Procurement
•Service
Management
Data
Integration

Data services
Flight
Planning
•Site selection
•Airspace
•Flight path
•Overlap
•Capture
parameters
Data
Acquisition
•Aircraft /
Platforms
•Sensors
•Computer
vision
•Embedded AI
Data
Processing
•On-board
•Cloud-based
•Post-
processing
•Live
streaming
•Storage
•Images/
video
•Photo-
grammetry
•3D models
•NDVI/ index
maps
•Machine
learning/AI
•Mobile
•PC
•Real-time data
•APIs
Data
Visualization
Data
Presentation
Operations
•Flight logging
•Fleet
management
•SOPs
•Safety checks
•Pre-flight / post-
flight
maintenance
•Insurance
Source:: Skylogic Research
•Asset
Management
(EAM)
•Operations
Management
•Procurement
•Service
Management
Data
Integration

Characteristics of drone
data
“Non-standard” IoT data
• Geospatial
• Images, videos, binaries
• Various file formats, indexes, metadata
• Require image analysis to support
• Requires transformation and parsing

Data types Raster
Pixels
TIFF, JPEG, etc.
Static and RDBMS friendly
Vector
Points, lines, polygons (XYZ and LAS)
Triangles represent the terrain surface
These are often combined, e.g., in a digital elevation model (DEM) which is
an image and vector data – 3D
Source: Wikipedia

Processed data Orthomosaic
Spectral / Thermal
Photogrammetry
LiDAR
Video
complexity

Orthomosaic
Unlike an uncorrected aerial
photograph, an orthophotograph can
be used to measure true distances,
because it is an accurate
representation of the Earth’s surface,
having been adjusted for topographic
relief, lens distortion, and camera tilt.
Orthomosaic - An orthophoto, orthophotograph or orthoimage is an aerial
photograph geometrically corrected (“orthorectified”) such that the scale is
uniform: the photo has the same lack of distortion as a map.
Source: Tim Boucher

Source: Wikipedia
Spectral imaging Spectral Imaging – Example: Normalized Difference Vegetation Index
(NDVI) is an index describing vegetation by showing the difference between
near-infrared (which is strongly reflected by vegetation) and red light (which
is absorbed by vegetation).

Source: RTF Drones
Thermal imaging Infrared thermography (IRT), thermal imaging, and thermal video cameras
detect radiation in the long-infrared range of the electromagnetic spectrum.
Building construction technicians can see thermal signatures that indicate
heat leaks in faulty thermal insulation and can use the results to improve the
efficiency of the final product.

Source: Tim Boucher
Photogrammetry Photogrammetry is a technique which uses photography to extract
measurements of the environment. This is achieved through the use of
overlapping imagery; where the same feature can be seen from two
perspectives it is possible to calculate measurements.

DEM Digital elevation model (DEM) is a digital model or 3D representation of a
terrain's surface created from terrain elevation data.
DSM: Digital Surface Model = (earth) surface including objects on it
DTM: Digital Terrain Model = (earth) surface without any objects
Source: Wikipedia

Image: Knowledge Center
Point cloud A point cloud is a set of data points in some coordinate system. In a three-
dimensional coordinate system, these points are usually defined by X, Y, and Z
coordinates, and often are intended to represent the external surface of an object.
Point clouds may be created by 3D scanners or photogrammetry software. These
measure a large number of points on an object's surface, and often output a point
cloud as a data file. The point cloud represents the set of points that the device
has measured.

Point cloud
Geometric dimensions and tolerances
can also be extracted directly from the
point cloud.
In geographic information system, point
clouds are one of the sources to make
digital elevation model of the terrain.
The point clouds are also employed in
order to generate 3D model of
construction environment. Image: ANRA Technologies

Image: HeMav
LiDAR LiDAR, which stands for Light Detection and Ranging, is a remote sensing
method that uses light in the form of a pulsed laser to measure ranges
(variable distances) to the Earth. These light pulses—combined with other
data recorded by the airborne system— generate precise, three-dimensional
information about the shape of objects and their surface characteristics.

BIM Building information modeling (BIM) is a process involving the generation
and management of digital representations of physical and functional
characteristics of places. Files are created which can be exchanged or
networked to support decision-making about a place.
One model, one map, one link.”
– Scott Widman, DPR Construction
Image: Asia Green Buildings

Video imaging Video is almost always stored in compressed form to reduce the file size for
storage. A video file normally consists of a container format (like MOV or
MP4) containing video data in a video coding format alongside audio data in
an audio coding format. This process is done using a Codec. Currently
h.264 is the predominant codec on the web.
The container format can also contain
synchronization information and
metadata such as GPS location and
directional data. This data can also be
encoded in each frame. There can be
24, 30, 60, 120, and even more frames
captured per second (FPS).
10 minutes of video at 30 fps = 18,000
frames

Video data analytics
What is happening?
• Is anything moving?
• Where does it go?
• When does it get to
someplace
interesting?
What is the value?
• Data to decisions
• Automation
• improves
exploitation of data
• Increases data
analysis efficiency
• Improves
performance
What can I see?
• How does it change
over time?
• How big is it?
• Where is it?
More GPU than CPU Source: Kitware

Artificial Intelligence (AI)

Image recognition

Machine learning
Chihuahua or Muffin?

Machine learning Maxim: Someone has to train the model
Maxim: All models are not perfect
Source: Nanonets

Deep learning Deep learning is a machine learning technique that teaches computers to do
what comes naturally to humans: learn by example.
In deep learning, a computer model
learns to perform classification tasks
directly from images, text, or sound.
Deep learning models can achieve
state-of-the-art accuracy, sometimes
exceeding human-level performance.
Models are trained by using a large set
of labeled data and neural network
architectures that contain many layers.
Image: Neurala

Predictive analytics
Source: Nanonets
Objective: detect the following
infrastructure to capture the
construction progress of a house in it’s
various stages :
1. foundation (start)
2. wallplate (in-progress)
3. roof (partially complete)
4. apron (finishing touches)
5. geyser (ready-to-move in).

Challenges and constraints There are several challenges to overcome when automating the analysis of
drone imagery. For example
1. Flat and small view of objects
2. Difficulty in labelling data
3. Large image sizes
4. Object overlap
Source: Nanonets

Vendors
Where to get this:
Go to my website droneanalyst.com
Got to ‘Research’
First ‘Industry Reports – Free’ tab

Vendors Drone Data / Image / Video Processing Software Market Share (2018
preliminary findings). Data represents over 112 brands.
21%
17%
17%
14%
7%
5%
2%
2%
1%
1%
1%
1%
1%
1%1%
9%
Adobe (Lightroom, Photoshop, Premiere, etc.)
Pix4D
DJI GO / GO4 / Skypixel
DroneDeploy
Apple (iPhoto, iMovie, Final Cut Pro, etc.)
Agisoft Photoscan
Drone2Map for ArcGIS (esri)
Maps Made Easy
PrecisionHawk
Bentley Systems
Trimble (Business Center / UASMaster)
DJI PC Ground Station
3DR Site Scan
Autodesk (Forge, ReCap, 123D)
DroneMapper
All others (less than 1%)
n = 1228
Source: Skylogic Research

Vendors Problems with Data, Image, and Video Processing Software (2018
preliminary findings)
11%
4%
5%
6%
9%
12%
13%
14%
15%
17%
20%
41%
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
All other problems
Image security for users or customers
NDVI accuracy
Reporting functions
Integration with the other downstream software
Composite image accuracy
Not enough analytics
Data upload process
Data export
App or software crashes
User interface / user-friendliness
Speed of processing
n = 579
Source: Skylogic Research

Stitching VENDOR 1
VENDOR 2
VENDOR 3
Source: William McNeil, Contributor / Advisor, Skylogic Research

Pricing Terms (freemium, monthly, annual, maps / month)
Sensor support
Algorithms / analytics
Tools (e.g. exports, APIs, 3rd party software pre-integration, GCPs, etc.)
Customer service / support

IT best practices for drone
data management
Data governance
Source aviation system access and APIs
Security and reliability along the “chain of custody”
Archive of source data for later re-processing
Master Data Management (MDM)
Privacy and risk mitigation
Access control
Source: Drone Analyst and SmartC2

Tip 1 Know your business objectives - and ensure your provider does, too.
Before signing up with a drone data mapping or imaging service
provider, make sure that provider is fully committed to understanding
the use case and the industry vertical you serve.
Not all do.
Some providers have more experience in one industry vs. another. For
example, they may promote the functionality to serve mining when in
fact their core functionality is based on serving agriculture.

Tip 2 Know who’s behind the curtain
Choosing a data service provider means you are choosing a business
partner.
Businesses come and go, and enterprises should ask hard questions
about the portability of their data to avoid lock-in or potential loss if the
business fails.
So, if you are interested in the long term viability of that partner it’s
always good to know who owns it, runs it, and funded it.
For some vendors, this is easy. For others it may take some digging.
For example, PrecisionMapper is owned by PrecisionHawk. That was
easy.
But did you know FarmSolutions is owned and run by the parent
company of Dronifi?

Tip 3 Pay attention to security, not just cost
Security and cost are also significant factors. Unfortunately, comparing
vendors' costs and security prowess isn't always easy. In many cases,
it's simply not an apples-to-apples comparison. What's more, tracking
down information related to a provider's costs and security strategy can
be tough, but here’s what you want to know:
• Access privileges: Service providers should be able to demonstrate
they enforce adequate hiring, oversight, and access controls to
enforce administrative delegation.
• Regulatory compliance: You and your enterprises client are
accountable for the data you collect -- even when it’s in a cloud
service. You should ensure the service provider you pick is ready
and willing to undergo audits.
• Data provenance – When selecting a provider, ask where their
datacenters are located and if they can commit to specific privacy
requirements – especially if you are serving agriculture. The farmer
will want to know.
• Data recovery – You must make sure your service provider has the
ability to do a complete restoration in the event of a disaster. Your
enterprise customer will ask

Tip 4 Check the box – When people ask me what’s the best drone service
my answer is always “the one that best meets your particular
requirements.” If you don’t already have a list of requirements, then it’s
time to get cracking. Here’s a starter list. Note that some of these may
not apply to the industry you want to serve:
• Mosaic creation
• Ortho-rectification
• 3D point clouds
• Digital elevation models -
including digital surface models
(DSM) and digital terrain models
(DTM)
• Crop health analysis tools (like
NDVI)
• Volume measurements (like
stockpiles)
• Plan overlays
• Change detection
• RTK / PPK support
• Manual or automatic shape
identification
• Feature extraction
• Object recognition
• Annotations
• Automated reporting and task
management tools
• APIs and outputs for use in GIS,
CAD and building information
modeling (BIM) software.
• Audit history
• Team collaboration
• Local coordinates
• Radiometric calculations
Not a complete
list of features

Tip 5 Evaluate their speeds and feeds
• How fast do you want results?
• How do you want to see it?
• Do you need a preview?
• Do you want to access and enjoy full functionality on a mobile app,
or is a using web browser all you need?
These all matter – and may matter more to your client than to you.

Review Role of software in drone operations
Characteristics of drone data (raw and processed)
Analytics and AI
Major vendors
Pricing
IT best practices
Five selection tips

Questions?

Managing Drone Data: Choosing the Right Data Service Provider

Recommandé

Recommandé

Contenu connexe

Plus de Colin Snow

Plus de Colin Snow (9)

Dernier

Dernier (20)

Managing Drone Data: Choosing the Right Data Service Provider